Health

Volume 8, Issue 1 (January 2016)

ISSN Print: 1949-4998   ISSN Online: 1949-5005

Google-based Impact Factor: 0.74  Citations  

Comparison of the Length of Stay and Medical Expenditures among Japanese Hospitals for Type 2 Diabetes Treatments: The Box-Cox Transformation Model under Heteroscedasticity

HTML  XML Download Download as PDF (Size: 380KB)  PP. 49-63  
DOI: 10.4236/health.2016.81007    5,004 Downloads   6,282 Views  Citations

ABSTRACT

In this paper, we analyzed length of stay (LOS) in hospitals and medical expenditures for type 2 diabetes patients. LOS was analyzed by the power Box-Cox transformation model when variances differed among hospitals. We proposed a new test and consistent estimator. We rejected the ho-moscedasticity of variances among hospitals, and then analyzed the LOS of 12,666 type 2 diabetes patients hospitalized for regular medical treatments collected from 60 general hospitals in Japan. The variables found to affect LOS were age, number of comorbidities and complications, introduced by another hospital, one-week hospitalization, 2010 revision, specific-hospitalization-period (SHP), and principal diseases E11.5, E11.6 and E11.7. There were surprisingly large differences in ALOS among hospitals even after eliminating the influence of characteristics and conditions of patients. We then analyzed daily medical expenditure (DME) by the ordinary least squares methods. The variables that affected DME were LOS, number of comorbidities and complications, acute hospitalization, hospital’s own outpatient, season, introduced by another hospital, one-week hospitalization, 2010 revision, SHP, time trend, and principal diseases E11.2, E11.4 and E117. The DME did not decrease after the SHP. After eliminating the influences of characteristics and conditions of patients, the differences among hospitals were relatively small, 12% of the overall average. LOS is the main determinant of medical expenditures, and new incentives to reduce LOS are needed to control Japanese medical expenditures. Since at least 99% of patients require medical care after leaving the hospital, systems that take proper care of patients for long periods of time after hospitalization are absolutely necessary for efficient treatment of diabetes.

Share and Cite:

Nawata, K. and Kawabuchi, K. (2016) Comparison of the Length of Stay and Medical Expenditures among Japanese Hospitals for Type 2 Diabetes Treatments: The Box-Cox Transformation Model under Heteroscedasticity. Health, 8, 49-63. doi: 10.4236/health.2016.81007.

Cited by

[1] Research on the Current Situation and Countermeasures of Inpatient Cost and Medical Insurance Payment Method for Rehabilitation Services in City S
Frontiers in Public Health, 2022
[2] Understanding variations and influencing factors on length of stay for T2DM patients based on a multilevel model
2021
[3] Estimation of Diabetes Prevalence, and Evaluation of Factors Affecting Blood Glucose Levels and Use of Medications in Japan
Health, 2021
[4] An Analysis of the Medical Costs of and Factors Affecting Diabetes Using the Medical Checkup and Payment Dataset in Japan: Can We Reduce the Prevalence …
2017
[5] An Analysis of the Medical Costs of and Factors Affecting Diabetes Using the Medical Checkup and Payment Dataset in Japan: Can We Reduce the …
2017
[6] Did the Revision of the Japanese Medical Payment System Work Properly?—An Analysis of Averages and Variances of Length of Hospital Stay for Type 2 Diabetes …
2016
[7] A Long Term Evaluation of the Japanese Medical Payment System for Cataract Surgeries: Did the Medical Policy Reduce the Long Hospital Stay in Japan?
2016
[8] Asymptotic Efficiency of the Maximum Likelihood Estimator for the Box-Cox Transformation Model with Heteroscedastic Disturbances
2016
[9] Did the Revision of the Japanese Medical Payment System Work Properly?—An Analysis of Averages and Variances of Length of Hospital Stay for Type 2 …
2016

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.